Triple
T9975933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian I, Count Palatine of Birkenfeld-Zweibrücken |
E196326
|
entity |
| Predicate | hasRegnalNumber |
P3023
|
FINISHED |
| Object | I |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: I | Statement: [Christian I, Count Palatine of Birkenfeld-Zweibrücken, hasRegnalNumber, I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegnalNumber Context triple: [Christian I, Count Palatine of Birkenfeld-Zweibrücken, hasRegnalNumber, I]
-
A.
tookRegnalName
Indicates that a person adopted and used a specific official regnal name upon assuming a throne or sovereign rulership.
-
B.
monarchNumber
chosen
Indicates the ordinal position or sequence number assigned to a monarch within a line of rulers.
-
C.
hasInscriptionFromReignOf
Indicates that an object bears an inscription created during the reign of a specified ruler or authority.
-
D.
royalDesignationYear
Indicates the year in which an entity was formally granted or recognized with a royal status or designation.
-
E.
epithetOfMonarchNumber
Indicates that a particular epithet (descriptive title or nickname) is associated with a specific numbered monarch in a royal succession.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84b47308190aa2f94fa7320cdc3 |
completed | April 2, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:48 p.m.